. The major function of this Core (RRC-A) is to support the research of two intervention studies in this OAIC, as well as that of pilot studies supported by the OAIC. A second function of RRC-A is to train young investigators in geriatrics and gerontology who are interested in research relevant to maintenance of functional independence of the elderly, in the performance of cost-effectiveness and cost-utility analyses. To the extent that investigators' time and the resources of the RRC-A permit, the RRC-A will also support other pilot and preliminary studies, as well as funded studies in geriatrics and gerontology. Use of this Core will be prioritized on the basis of the relevance of the research to the goal of this OAIC, which is to find effective means of preventing and reversing physical frailty and maintaining functional independence of the elderly. The specific functions of RRC-A are to: a) recruit subjects for participation in the intervention studies planned, IS-1 and IS-2, and the pilot studies in the Research Development Core; b) perform screening assessments of subjects to identify those eligible for the studies, including physical examination with neurological assessment, SMA-12 blood chemistries, a complete blood count, urinalysis, PA chest x-ray, and a resting 12-lead ECG; c) perform interview assessments that include demographic, psychosocial, psychometric, physical activity, functional status, tall history, and quality of life measures for use in IS-1, IS-2, and the pilot studies; d) collect data on health care utilization and utility measures for IS-1, IS-2, and the pilot studies; and e) conduct cost-effectiveness and cost-utility analyses of the interventions. Performing these procedures in RRC-A instead of in each of the intervention studies is to increase efficiency by eliminating the need to have personnel trained in the performance of the procedures in each of the studies. Furthermore, having all the assessments performed by the same research team is intended to enhance data quality by decreasing data variability.